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Modern Computer Vision with PyTorch. A practical roadmap from deep learning fundamentals to advanced applications and Generative AI - Second Edition

(ebook) (audiobook) (audiobook) Książka w języku 1
Modern Computer Vision with PyTorch. A practical roadmap from deep learning fundamentals to advanced applications and Generative AI - Second Edition V Kishore Ayyadevara, Yeshwanth Reddy - okladka książki

Modern Computer Vision with PyTorch. A practical roadmap from deep learning fundamentals to advanced applications and Generative AI - Second Edition V Kishore Ayyadevara, Yeshwanth Reddy - okladka książki

Modern Computer Vision with PyTorch. A practical roadmap from deep learning fundamentals to advanced applications and Generative AI - Second Edition V Kishore Ayyadevara, Yeshwanth Reddy - audiobook MP3

Modern Computer Vision with PyTorch. A practical roadmap from deep learning fundamentals to advanced applications and Generative AI - Second Edition V Kishore Ayyadevara, Yeshwanth Reddy - audiobook CD

Serie wydawnicze:
Learning
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
746
Dostępne formaty:
     PDF
     ePub
Whether you are a beginner or are looking to progress in your computer vision career, this book guides you through the fundamentals of neural networks (NNs) and PyTorch and how to implement state-of-the-art architectures for real-world tasks.

The second edition of Modern Computer Vision with PyTorch is fully updated to explain and provide practical examples of the latest multimodal models, CLIP, and Stable Diffusion.

You’ll discover best practices for working with images, tweaking hyperparameters, and moving models into production. As you progress, you'll implement various use cases for facial keypoint recognition, multi-object detection, segmentation, and human pose detection. This book provides a solid foundation in image generation as you explore different GAN architectures. You’ll leverage transformer-based architectures like ViT, TrOCR, BLIP2, and LayoutLM to perform various real-world tasks and build a diffusion model from scratch. Additionally, you’ll utilize foundation models' capabilities to perform zero-shot object detection and image segmentation. Finally, you’ll learn best practices for deploying a model to production.

By the end of this deep learning book, you'll confidently leverage modern NN architectures to solve real-world computer vision problems.

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O autorach książki

V Kishore Ayyadevara leads a team focused on using AI to solve problems in the healthcare space. He has 10 years' experience in data science, solving problems to improve customer experience in leading technology companies. In his current role, he is responsible for developing a variety of cutting edge analytical solutions that have an impact at scale while building strong technical teams. Prior to this, Kishore authored three books — Pro Machine Learning Algorithms, Hands-on Machine Learning with Google Cloud Platform, and SciPy Recipes. Kishore is an active learner with keen interest in identifying problems that can be solved using data, simplifying the complexity and in transferring techniques across domains to achieve quantifiable results.
Yeshwanth Reddy is a data scientist with prior teaching experience in INSOFE. He has completed his M.Tech and B.Tech from IIT Madras.

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